A variational perspective on noise-robust speech recognition

Model compensation methods for noise-robust speech recognition have shown good performance. Predictive linear transformations can approximate these methods to balance computational complexity and compensation accuracy. This paper examines both of these approaches from a variational perspective. Using a matched-pair approximation at the component level yields a number of standard forms of model compensation and predictive linear transformations. However, a tighter bound can be obtained by using variational approximations at the state level. Both model-based and predictive linear transform schemes can be implemented in this framework. Preliminary results show that the tighter bound obtained from the state-level variational approach can yield improved performance over standard schemes. © 2011 IEEE.

Derivative kernels for noise robust ASR

Recently there has been interest in combining generative and discriminative classifiers. In these classifiers features for the discriminative models are derived from the generative kernels. One advantage of using generative kernels is that systematic approaches exist to introduce complex dependencies into the feature-space. Furthermore, as the features are based on generative models standard model-based compensation and adaptation techniques can be applied to make discriminative models robust to noise and speaker conditions. This paper extends previous work in this framework in several directions. First, it introduces derivative kernels based on context-dependent generative models. Second, it describes how derivative kernels can be incorporated in structured discriminative models. Third, it addresses the issues associated with large number of classes and parameters when context-dependent models and high-dimensional feature-spaces of derivative kernels are used. The approach is evaluated on two noise-corrupted tasks: small vocabulary AURORA 2 and medium-to-large vocabulary AURORA 4 task. © 2011 IEEE.

Extending noise robust structured support vector machines to larger vocabulary tasks

This paper describes a structured SVM framework suitable for noise-robust medium/large vocabulary speech recognition. Several theoretical and practical extensions to previous work on small vocabulary tasks are detailed. The joint feature space based on word models is extended to allow context-dependent triphone models to be used. By interpreting the structured SVM as a large margin log-linear model, illustrates that there is an implicit assumption that the prior of the discriminative parameter is a zero mean Gaussian. However, depending on the definition of likelihood feature space, a non-zero prior may be more appropriate. A general Gaussian prior is incorporated into the large margin training criterion in a form that allows the cutting plan algorithm to be directly applied. To further speed up the training process, 1-slack algorithm, caching competing hypothesis and parallelization strategies are also proposed. The performance of structured SVMs is evaluated on noise corrupted medium vocabulary speech recognition task: AURORA 4. © 2011 IEEE.

Physical modelling of flexible retaining walls under seismic actions

A series of dynamic centrifuge tests on reduced scale models of flexible retaining structures were conducted on the Turner beam centrifuge at the Schofield Centre of the University of Cambridge. The paper illustrates the main results of the experimental work in terms of observed amplifications of ground motion and mobilised shear stiffness and damping ratio for all tests. The experimental results for one test on a pair of cantilevered walls in dense sand are also presented in terms of measured bending moments and horizontal displacements of the walls during (maximum values) and at the end of (residual values) each seismic event. Finally, the experimental data are discussed in the light of the results obtained from dynamic numerical analyses of the behaviour of cantilevered walls under real seismic actions. © 2010 Taylor & Francis Group, London.

Gaussian Process training with input noise

In standard Gaussian Process regression input locations are assumed to be noise free. We present a simple yet effective GP model for training on input points corrupted by i.i.d. Gaussian noise. To make computations tractable we use a local linear expansion about each input point. This allows the input noise to be recast as output noise proportional to the squared gradient of the GP posterior mean. The input noise variances are inferred from the data as extra hyperparameters. They are trained alongside other hyperparameters by the usual method of maximisation of the marginal likelihood. Training uses an iterative scheme, which alternates between optimising the hyperparameters and calculating the posterior gradient. Analytic predictive moments can then be found for Gaussian distributed test points. We compare our model to others over a range of different regression problems and show that it improves over current methods.

Seismic response of stone masonry spires: Analytical modeling

Stone masonry spires are vulnerable to seismic loading. Computational methods are often used to predict the dynamic linear elastic response of masonry towers and spires, but this approach is only applicable until the first masonry joint begins to open, limiting the ability to predict collapse. In this paper, analytical modeling is used to investigate the uplift, rocking and collapse of stone spires. General equations for static equilibrium of the spire under lateral acceleration are first presented, and provide a reasonable lower bound for predicting collapse. The dynamic response is then considered through elastic modal analysis and rigid body rocking. Together, these methods are used to provide uplift curves and single impulse overturning collapse curves for a complete range of possible spire geometries. Results are used to evaluate the historic collapse of two specific stone spires. © 2012 Elsevier Ltd.

Seismic response of stone masonry spires: Computational and experimental modeling

Analytical methods provide a global context from which to understand the dynamics of stone spires, but computational and experimental methods are useful to predict more specific behavior of multiple block structures. In this paper, the spire of St. Mary Magdalene church in Waltham-on-the-Wolds, UK, which was damaged in the 2008 Lincolnshire Earthquake, is used as a case study. Both a physical model and a discrete element computational model of the spire were created and used to investigate collapse under constant horizontal acceleration, impulse base motion, and earthquake ground motion. Results indicate that the global behavior compares well with analytical modeling, but local block displacements evident in DEM and experimental results also reduce the stability of the structure. In this context, the observed damage to St. Mary Magdalene church is evaluated and discussed. © 2012 Elsevier Ltd.

Dual gate photo-thin film transistor with high photoconductive gain for high reliability, and low noise flat panel transparent imager

In this presentation, we report excellent electrical and optical characteristics of a dual gate photo thin film transistor (TFT) with bi-layer oxide channel, which was designed to provide virgin threshold voltage (V T) control, improve the negative bias illumination temperature stress (NBITS) reliability, and offer high photoconductive gain. In order to address the photo-sensitivity of phototransistor for the incoming light, top transparent InZnO (IZO) gate was employed, which enables the independent gate control of dual gate photo-TFT without having any degradation of its photosensitivity. Considering optimum initial V T and NBITS reliability for the device operation, the top gate bias was judiciously chosen. In addition, the speed and noise performance of the photo-TFT is competitive with silicon photo-transistors, and more importantly, its superiority lies in optical transparency. © 2011 IEEE.

Seismic analyses of shallow tunnels by dynamic centrifuge tests and finite elements

The increments of internal forces induced in a tunnel lining during earthquakes can be assessed with several procedures at different levels of complexity. However, the substantial lack of well-documented case histories still represents a difficulty in order to validate any of the methods proposed in literature. To bridge this gap, centrifuge model tests were carried out on a circular aluminium tunnel located at two different depths in dense and loose dry sand. Each model has been instrumented for measuring soil motion and internal loads in the lining and tested under several dynamic input signals. The tests performed represented an experimental benchmark to calibrate dynamic analyses with different approaches to account for soil-tunnel kinematic interaction. © 2009 IOS Press.

Contra-rotating open rotor operation for improved aerodynamics and noise at takeoff

The contra-rotating open rotor is, once again, being considered as an alternative to the advanced turbofan to address the growing pressure to cut aviation fuel consumption and carbon dioxide emissions. One of the key challenges is meeting community noise targets at takeoff. Previous open rotor designs are subject to poor efficiency at takeoff due to the presence of large regions of separated flow on the blades as a result of the high incidence needed to achieve the required thrust. This is a consequence of the fixed rotor rotational speed constraint typical of variable pitch propellers. Within the study described in this paper, an improved operation is proposed to improve performance and reduce rotorrotor interaction noise at takeoff. Three-dimensional computational fluid dynamics (CFD) calculations have been performed on an open rotor rig at a range of takeoff operating conditions. These have been complemented by analytical tone noise predictions to quantify the noise benefits of the approach. The results presented show that for a given thrust, a combination of reduced rotor pitch and increased rotor rotational speed can be used to reduce the incidence onto the front rotor blades. This is shown to eliminate regions of flow separation, reduce the front rotor tip loss and reduce the downstream stream tube contraction. The wakes from the front rotor are also made wider with lower velocity defect, which is found to lead to reduced interaction tone noise. Unfortunately, the necessary increase in blade speed leads to higher relative Mach numbers, which can increase rotor alone noise. In summary, the combined CFD and aero-acoustic analysis in this paper shows how careful operation of an open rotor at takeoff, with moderate levels of re-pitch and speed increase, can lead to improved front rotor efficiency as well as appreciably lower overall noise across all directivities. Copyright © 2011 by ASME.